This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 9721–9740 of 16897 papers
Luís Otero González, Diego Alaiz Crespo, Pablo Duran Santomil +1
This paper evaluates the effectiveness of ESG engagement by mutual funds in mitigating environmental impact and addressing climate change. Using quarterly data from 1,600 US mutual funds (2019–2022), it compares voting patterns on environme…
Chocoroua Omar, Fumiaki Inagaki, Ayako Watanabe
This study analyzes household cooking fuel choices in Mozambique's energy-rich peripheries. Rising income increases electricity/LPG adoption; price is a strong negative predictor. Infrastructure reliability matters: households with energy i…
Jorge Ruso, Diego Portalanza, Patricio Alvarez-Muñoz +1
This study provides the first integrated, integrity-centered cross-mechanism analysis of Ecuador's carbon credit market, covering CDM, REDD+, and the voluntary carbon market (VCM). Using an institutional economics framework, it finds that u…
Lira Luz Benites Lázaro, Rosie Day
This review maps 2,505 publications on gender in energy justice and just transitions using bibliometrics, BERTopic, and qualitative analysis. It reveals a focus on justice, energy communities, and acceptance, while critical areas like miner…
Mariusz Kudełko
This paper conducts a cost-benefit analysis of decarbonising the Polish energy sector to 2050. It finds that full decarbonisation is socially optimal only at an SCC of approximately €165/tCO2, requiring an estimated €228 billion in investme…
Xin Hui Cheng, Irene Moser, Stephen Doliente +2
This paper presents a multi-vector, multi-nodal optimization model for least-cost capacity expansion and retirement planning, applied to Sarawak, Malaysia. Results show perfect foresight enables smoother transitions at lower cost, while myo…
Bayat M, Azad MT, Lari K +2
This paper proposes a digital twin framework that integrates high-resolution marine microclimate modeling (salt deposition, humidity, sea-breeze) with techno-economic optimization for coastal hybrid renewable energy systems. Applied to Kish…
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This paper analyzes the impact of carbon tax on economic growth and environmental quality. Carbon taxes are effective for GHG reduction but may have negative economic consequences.
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This paper focuses on data quality issues in Scope 3 emissions and proposes machine learning prediction methods. It aims to improve accuracy in estimating supply chain-wide emissions.
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This paper proposes a framework linking supply chain finance with carbon accounting data, enabling companies to incorporate emission data into financial terms and incentivize decarbonization across the supply chain. While specific methods a…
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This paper empirically examines the impact of climate change disclosure on firms' cost of capital, finding that higher-quality disclosure is associated with lower cost of capital, highlighting investor valuation of transparency.
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This paper empirically analyzes the factors driving firms' adoption of TCFD recommendations and the performance effects of such adoption, providing insights into the determinants and financial impacts of climate disclosure.
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This paper empirically examines whether green finance drives firms to translate ESG talk into concrete action. It investigates the effectiveness of green finance in promoting genuine corporate ESG practices and identifies conditions under w…
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This paper proposes a machine learning approach to predict ESG ratings. It builds models that estimate ESG scores from publicly available corporate data and compares performance with traditional methods. The research contributes to automati…
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This study proposes and validates a machine learning-based approach to analyze corporate climate disclosures, highlighting the use of AI for assessing disclosure quality and compliance.
Qorriyeva Shahnoza Safarbayevna
This paper analyzes green project financing in Uzbekistan. From 2020-2024, renewable capacity grew to ~5,434 MW, SDG bonds of USD 235M and a sovereign green Eurobond of USD 350M were issued. However, regulatory, capital market, and transmis…
Adel Elgammal
This study proposes a hybrid floating offshore wind-solar platform and validates its design using an AI optimization framework combining machine learning, deep reinforcement learning, and genetic algorithms. Results show 32% higher energy o…
Xu S.
This paper comprehensively reviews challenges and emerging trends in hydrogen energy industrialization. It covers the entire process from hydrogen evolution reaction to storage, transportation, and utilization, discussing technical barriers…
Zhang Y.
This paper proposes methods to apply artificial intelligence to optimize the operation of thermal power plants, thereby reducing carbon dioxide emissions. By utilizing AI, it is possible to improve combustion efficiency and reduce downtime …
Goudar P.S.
This paper proposes the electrolysis of cow urine as a method for producing green hydrogen, integrating waste treatment with energy generation. The approach aligns with circular economy principles by converting a waste product into a valuab…
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